Multiplicity distributions and rapidity gaps

Abstract

We examine the phenomenology of particle multiplicity distributions, with special emphasis on the low multiplicities that are a background to the study of rapidity gaps. In particular, we analyze the multiplicity distribution in a rapidity interval between two jets, using the HERWIG QCD simulation with some necessary modifications. The distribution is not of the "negative binomial" form, and displays an anomalous enhancement at zero multiplicity. Some useful mathematical tools for working with multiplicity distributions are presented. It is demonstrated that ignoring particles with p ⊥ < 0.2 GeV/c has theoretical advantages, in addition to being convenient experimentally.

Using rapidity gaps to distinguish between Higgs boson production byWand gluon fusion

“…Besides those problems, there are others that will not be discussed here such as gaps produced by statistical fluctuations in the background events, gaps produced by other color singlet scattering (such as W W → Z → ZZ) and the most common ones, diffractive scatterings. These problems have already been studied by many authors [4,5,6,7] and do not address the problem investigated in this paper, which is the use of rapidity gaps to distinguish between higgs production by gluon and W fusion.…”

Analysis of charged-particle–photon correlations in hadronic multiparticle production

“…We next generalize this formalism to bivariate distributions of charged and neutral pions. Among our motivations for doing this is the simple manner in which detection inefficiencies and particle decays can be handled with generating functions [27]. These features are particularly important in dealing with the MiniMax experimental situation.…”

“…The generating function formalism has been widely used to study chargedhadron multiplicity distributions [16][17][18][19][20]27]. We next generalize this formalism to bivariate distributions of charged and neutral pions.…”

“…With sufficiently large statistics we can determine probabilities, p(n ch , n γ ), for observing these combinations over some portion or all of the available phase space. In order to obtain the charged-pion/photon generating function, incorporating both π ± and γ detection efficiencies from G(z ch , z 0 ), we extend Pumplin's cluster theorem [27] to the bivariate case. Consider a generating function G(z ch , z 0 ) that refers to charged and neutral "clusters."…”

“…It is often useful to express P (N) as a Poisson transform [27] where one introduces a spectral representation in terms of Poisson distributions with a weighting function ρ(µ):…”